Machine Learning Engineer II

Overview

Abnormal AI is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection team. At Abnormal, we protect our customers against adversaries who are constantly evolving their techniques and tactics to outwit traditional security approaches. Abnormal has been named one of the top cybersecurity startups and our behavioral AI system has helped us earn various cybersecurity accolades, resulting in trusted protection for more than 25% of the Fortune 500 (and growing).

In a landscape where a single successful attack can lead to financial losses, the Attack Detection team builds an extremely high-recall Detection Engine that can operate on hundreds of millions of messages at millisecond latency. The team’s mission is to provide world-class detector efficacy to tackle a changing attack landscape using a combination of generalizable and auto-trained models, as well as specific detectors for high-value attack categories.

This team solves a multi-layered detection problem by modeling communication patterns to establish enterprise baselines, incorporating these patterns as robust signals, and combining them with contextual information to create precise systems. Signals are built at various levels including message level, sender level, and recipient level, and are used to train both model-based and heuristic detectors. The team also supports automated model retraining pipelines, including data analytics and generation stages, modeling stages, production evaluation stages, and automated deployment stages.

This role offers the opportunity to influence the team’s charter, direction, and roadmap. The Machine Learning Engineer will help understand the domain of false negatives—current and future attacks that can disrupt customer workflows—and define the technical roadmap required to address the most pressing customer problems while operating the detection decisioning system at very high recall.

• Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance.
• Understand features that distinguish safe emails from email attacks, and how the model stack enables detection.
• Identify and recommend new feature groups or ML model approaches to significantly improve detection efficacy. Work with infrastructure and systems engineers to product ionize signals for the detection system.
• Write code with testability, readability, edge cases, and error handling in mind.
• Train models on well-defined datasets to improve efficacy on specialized attacks.
• Actively monitor and improve FN rates and efficacy for the message detection product attack categories through feature engineering, rules, and ML modeling.
• Analyze FN and FP datasets to identify capability gaps and recommend short-term feature and rule ideas to improve detection efficacy.
• Contribute in other areas of the stack, including building and debugging data pipelines or presenting results to customers when appropriate.

• 3+ years of experience designing, building, and deploying machine learning applications in text understanding, NLP, computer vision, recommendation systems, or search.
• 1+ year of experience with writing stable, production-level pipelines for model training and evaluation leading to reproducible models and metrics.
• Experience with data analytics and using SQL, pandas, and Spark to build data and metric generation pipelines and answer questions about system efficacy.
• Ability to understand business requirements and design a simple yet generalizable ML model/system to achieve the goal.
• Systematic approach to debugging data and system issues within ML/heuristics models.
• Fluent with Python and ML toolkits such as Num Py, scikit-learn, PyTorch, and Tensor Flow.
• Effective software engineering skills with the ability to read code, write structured, well-tested, efficient code.
• BS degree in Computer Science, Applied Sciences, Information Systems, or related engineering field.

• MS degree in Computer Science, Electrical Engineering, or related field.
• Experience with big data, statistics, and machine learning.
• Experience with algorithms and optimization.

This position is not:

• A role focused on optimizing existing machine learning models
• A research-oriented role disconnected from the product or customer
• A statistics/data science meets ML role

Base salary range: $168,300 — $198,000 USD

Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement, please review the company policy on EEO rights under the law.